Hello, I need to build a dense matrix in parallel and looking at examples in ksp/examples/tutorials it seems there are two approaches. In ex3.c MPI_Comm_rank and MPI_Comm_size are used to compute the index range for the current processor and ex5.c uses MatGetOwnershipRange to figure out the index range. 1- Is there any advantage using either of these methods or they will behave the same when it comes to performance and portability ? Based on comments in ex5.c, PETSc partitions the matrix by contiguous chunks of rows. 2- Is there a way of changing this scheme using PETSc routines ? 3- If not, can I partition my matrix in a different way, say 2D block cycling method, and still be able to use PETSc to solve it ? Since my matrix is dense I am going to start with direct solvers and I am concerned whether the partitioning scheme will affect the solver's performance. thanks in advance, Hamid